# coding=utf-8
# Copyright 2024 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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#     http://www.apache.org/licenses/LICENSE-2.0
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"""Custom losses."""
import torch.nn as nn


def categorical_cross_entropy(pred_logits, y_true_softmax):
  """Categorical cross entropy."""
  log_softmax_pred = nn.LogSoftmax(dim=1)(pred_logits)
  soft_targets = y_true_softmax.detach().clone()  # Stop gradient
  cce_loss = -(soft_targets * log_softmax_pred).sum(dim=1).mean()
  return cce_loss
